1. Overview

For every data visualization in Dundas BI, there is an underlying metric set that encapsulates the data, and there are settings that determine how each element in the data is visualized.

The visualization options are different depending on the type. A bar chart, for instance, has a number of options for each series of bars, such as:

Bar Height - lets you specify the measure that determines the height of each data point bar

Horizontal Axis - lets you specify what values determine the position of each data point bar along the x axis

Description - lets you specify what measures or hierarchies should identify this series in the legend or a series label

Tooltip - lets you specify values to be displayed in a popup when the user hovers over or long-taps a data point

Data Point Label - lets you specify values to display in data point labels

Color - lets you change the colors of data points based on the values you select

Note - lets you specify values to display as notes, the same way user-added notes or annotations are displayed

Series Grouping - lets you specify or remove hierarchies used to group this series into multiple series

Side-By-Side Position - lets you specify a hierarchy that determines if series are displayed side-by-side or on top of other series based on matching values

Other chart types and other data visualization types have different options (although there may be some in common).

The visualization options are always specific to that instance of a visualization. A metric set created in the full-screen editor can have different visualization settings than the same metric set dragged onto the dashboard and then customized in the dashboard editor. A metric set can also be dragged onto a dashboard multiple times and each can be visualized differently.

2. Metric set editor

2.1. Default visualization

When you create a new metric set from the main menu, you have the ability to configure a visualization for that metric set. This visualization serves as a template for a new data visualization instance when you drag this metric set from the Explore window onto a dashboard canvas, although from then on the two visualizations are separate.

You can set up how each metric set element is visualized by clicking the Visualization button in the Data Analysis Panel.

In the Visualization tab, you can see the various mappings that were assigned automatically when measures and hierarchies were first added to the metric set. In the example below, the LineTotal measure and the OrderDate hierarchy were automatically added under Tooltip Text for Series 1.

2.2. Assign elements to an option

There are several ways to assign a measure or hierarchy to a visualization option.

Drag from the Explore window: drag a measure or hierarchy (or hierarchy level) from the Explore window and drop it under an option in the Visualization tab (similar to adding elements to the metric set).

Drag within the Visualization tab: drag a measure or hierarchy already selected elsewhere in the Visualization tab and drop it where you want to add it. Note that if you press the Shift key while you drag within the Visualization tab, this will actually move the measure/hierarchy from one option to another.

Click to add: use the click to add link in the Visualization's drop region and select the measure or hierarchy you want from a list.

Next, if you drag this metric set onto the canvas of a dashboard, the resulting bar chart will also display data point labels because of this setting in the metric set's default visualization.

Note

If you use a measure or hierarchy that is not part of the metric set to configure the Visualization tab, the metric set will be automatically updated with the new measure/hierarchy. You can see this by clicking the Metric Set button at the top of the Visualization tab, which takes you back to the Metric Set definition.

2.3. Configure a measure or hierarchy

From the Visualization tab, click the Edit button of any measure or hierarchy to configure the corresponding metric set element.

This opens the Configure Metric Set Element dialog, which lets you see where the visualization is using this measure/hierarchy, and change metric set settings for this measure. For example, you can specify a dollar sign as a symbol that appears before LineTotal values.

Note that when you're configuring a metric set element, these settings are part of the metric set itself and not the visualization. This means that in order to view or change certain settings for the metric set element, the corresponding metric set must be checked out to you. In addition, changes to the metric set element, such as adding a symbol or changing the format string, will apply to all data visualizations connected to the metric set.

3. Editing dashboards and other views

When you drag a metric set from the Explore window to the canvas of a dashboard or another view, a new data visualization instance is created with the default visualization settings and appearance. For example, in the figure below, observe that the newly added bar chart displays data point labels just like the metric set's default visualization.

3.1. Launching the Data Analysis Panel

The Data Analysis Panel is open by default when adding a new data visualization instance, but will close if you click away. To open the Data Analysis Panel, use the context menu, or select the data visualization on the canvas and click the Data Analysis Panel button in the toolbar.

The Data Analysis Panel is the same as the panel in the full-screen metric set editor, except that in the Visualization tab you're viewing and editing settings specific to this data visualization on the dashboard (instead of the metric set's own default visualization).

3.2. Data visualization drop zones

An easy way to configure the Visualization tab is to drag a measure, hierarchy, or hierarchy level from the Explore window and drop it onto a data visualization drop zone. These drop zones are overlays that appear over a data visualization and correspond directly to the visualization settings. The available drop zones are different depending on the type of data visualization, whether you're adding a measure or hierarchy, and where data has already been assigned. Note that drop zones only appear if some initial data has already been added to the data visualization beforehand. For example, in the figure below, a LineTotal measure has already been added to the table.

3.3. Update the default visualization

Once you've customized a data visualization instance, you can apply the settings back to the metric set's default visualization by clicking the Update button in the Data Analysis Panel. After the update, the next time this metric set is dragged to the canvas, the newly added data visualization will be of the same type and have the same settings as the updated default visualization.

3.4. Properties window

You can use the Properties window for a data visualization to customize the settings of the visualization itself, including further customizing how the visualization displays data you've assigned in the Data Analysis Panel. For example, you can customize how the colors of the data points should change according to the data. For text properties, you can use the Properties window to customize how the data is formatted into text.

As an example, consider a bar chart that does not have any measures assigned to its Series 1 Data Point Label setting. Go to the Properties window for the chart series, click the Text tab, and you'll see that there are no data point labels for this chart.

Now go back to the Properties window for the chart series, click the Text tab, and you'll see that data point label settings have been automatically added. Alternatively, you can add these data label settings manually to the chart series.

Click Data Label Settings to customize the placement of the labels, and the text to display. The Text property has been automatically populated based on the data you assigned, but you are able to change it to include any arbitrary text in addition to one or more placeholder keywords (such as the name of a measure or hierarchy) enclosed in square brackets, and you can also customize the value's formatting. See Formatting text for details on how you can set text properties using placeholder keywords.